HPC Performance Engineer - Optimize Compilers & GPU Apps

NVIDIA Corporation

Oregon (WI)

Hybrid

USD 152,000 - 241,500

Full time

14 days+

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Job summary

NVIDIA Corporation in the United States is seeking an HPC Performance Engineer within the NVHPC compilers & tools group to analyze high‑performance workloads and drive performance improvements through compiler optimizations and library enhancements.

You will evaluate the impact of compilers and runtimes on CPU and CPU/GPU platforms, port applications to varied architectures, and collaborate with application engineers to push scalable performance.

Qualifications

  • BS/MS or equivalent experience in Computer Science or a related engineering field.
  • 5+ years of programming experience.
  • Strong understanding of Fortran, C, C++, and programming techniques, especially for parallel architectures, preferably for compilers.
  • Experience with OpenACC, OpenMP, MPI, CUDA and Standard Language Parallelism.
  • Strong mathematical fundamentals, including linear algebra and numerical methods.

Responsibilities

  • Analyze the effect of different compilers and compiler optimizations on HPC application performance.
  • Evaluate whether and how the compiler and runtime can improve performance on CPU and CPU/GPU platforms.
  • Communicate limits of compiler capabilities with application engineering to guide improvements.
  • Port HPC applications to different platforms and programming models.
  • Evaluate the impact of NVHPC package components, device driver, and system configuration on performance.

Skills

Fortran, C, C++
Parallel programming
Performance analysis
Communication

Education

BS/MS in CS or related field

Tools

OpenACC
OpenMP
MPI
CUDA

Job description

NVIDIA Corporation in the United States is seeking an HPC Performance Engineer within the NVHPC compilers & tools group to analyze high‑performance workloads and drive performance improvements through compiler optimizations and library enhancements.

You will evaluate the impact of compilers and runtimes on CPU and CPU/GPU platforms, port applications to varied architectures, and collaborate with application engineers to push scalable performance.

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